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Comentários e feedback de alunos de modelos de sequência da instituição deeplearning.ai

4.8
estrelas
27,682 classificações
3,306 avaliações

Sobre o curso

In the fifth course of the Deep Learning Specialization, you will become familiar with sequence models and their exciting applications such as speech recognition, music synthesis, chatbots, machine translation, natural language processing (NLP), and more. By the end, you will be able to build and train Recurrent Neural Networks (RNNs) and commonly-used variants such as GRUs and LSTMs; apply RNNs to Character-level Language Modeling; gain experience with natural language processing and Word Embeddings; and use HuggingFace tokenizers and transformer models to solve different NLP tasks such as NER and Question Answering. The Deep Learning Specialization is a foundational program that will help you understand the capabilities, challenges, and consequences of deep learning and prepare you to participate in the development of leading-edge AI technology. It provides a pathway for you to take the definitive step in the world of AI by helping you gain the knowledge and skills to level up your career....

Melhores avaliações

JY

29 de out de 2018

The lectures covers lots of SOTA deep learning algorithms and the lectures are well-designed and easy to understand. The programming assignment is really good to enhance the understanding of lectures.

AM

30 de jun de 2019

The course is very good and has taught me the all the important concepts required to build a sequence model. The assignments are also very neatly and precisely designed for the real world application.

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676 — 700 de 3,306 Avaliações para o modelos de sequência

por SHIVAM K

14 de fev de 2021

I learned various applications of the sequence models. I hope, I will be able to solve various problems by applying the techniques I have learned.

por Armaan B

11 de set de 2019

Andrew Ng does not hold anything back while discussing sequence models, including attention mechanisms and how to process and generate audio data.

por wadigzon D

24 de fev de 2019

excellent, I did some speech recognition & neural nets in the past, I am surprised at how much the field has evolved, this was a great refreshener

por Yashwanth R V

20 de fev de 2018

The specialisation and this course have truly helped me gain a profound knowledge in theory as well as in programming of the Deep Learning models.

por BRAYAN Z

11 de out de 2020

Course with great content, great examples that give you great intuition and capabilities to enter how the RNN and its different applications work

por Bruno F B V

7 de jan de 2020

It has been a long way, but in my opinion this is one of the best set of courses related to Deep Learning someone can find on the internet today.

por Daniel W

30 de set de 2019

The course really well introduces to the key concepts of machine learning sequence modelling and NLP tasks. Furthermore, it is really up-to-date.

por Chenkuan L

24 de dez de 2020

Very nice course on recurrent neural network and natural language processing using deep learning. Andrew's lectures are both clear and engaging.

por Devavrat S B

9 de jun de 2020

The course is very good for understanding RNN, GRU, LSTM from basics along with word embedding. Thank you Andrew Ng Sir for such a great course.

por Michel M

28 de set de 2019

This module didn't look as prepared than the others. The assignments had far more errors than the others and also the video were less compelling

por Anirudh A

1 de set de 2019

Awesome course, taking the student from basics to the advanced level seamlessly. I Really learnt a lot from this. Thanks Andrew Ng and team. :)

por Murad O

13 de fev de 2018

I find this course much better done and prepared than the course on ConvNets. I also learned much here and found it interesting and educational.

por 18IT042 C J

23 de jun de 2020

This specialisation was very informative, and I learned a lot of things from these courses. Thanks to Coursera and Deeplearning.ai to teach me.

por Fahad S

17 de set de 2018

This course teaches relatively advanced courses in a very intuitive manner. The assignments were challenging yet fun. Highly recommended course

por Reinaldo L N

3 de abr de 2018

simplesmente espetacular. São as palavras que eu encontro para descrever toda a sequência de cursos do Andrew Ng. Mas tem que AMAR matemática !

por Jiansen.Zheng

14 de fev de 2018

Pretty good, for learning recurrent neural network and neural machine translation, and I learned a lot about Keras in the program assignments.

por Diego B C d S

28 de dez de 2020

O curso tem o balanço perfeito entre teoria e prática. Tudo muito completo, mostrando os detalhes para se entender Deep Learning. Muito Bom!!!

por Sadanand M

7 de jun de 2020

Excellent exercises and assignments! And most importantly, Prof. Andrew Ng's teaching style is superb and has made me quite an admirer of him.

por Bhabani D

6 de abr de 2020

Clear but concise , Which is really helpful for busy professionals. the course tests are really useful in conveying the message of the course.

por Njabulo M

23 de ago de 2019

I was really hoping this course would focus more on time series data. Still a great course if you are interested in speech recognition and NLP

por Chuck H

23 de mai de 2018

Really well taught course. I felt like the programming assignments were too easy. I think its one of the best deep learning courses out there.

por Jimmy I

30 de abr de 2018

Impressive amount of work to prepare the course material. I enjoy the learning immensely. It saves me a lot of time from reading white papers.

por Tom Z

12 de abr de 2018

The course is really helpful. The whole series helped me get a sense of what is deep leawrning and how CNN and RNN work in different contexts.

por Tian Y

4 de mar de 2021

I'm so grateful for NG, cos these courses help me step into DL. If someday I have my own paper, I will come back here to share my happiness.

por Ali H D

10 de abr de 2020

One of the best courses I have taken. The great balance between theory and practice(assignments) is so well done and on point. Thanks Andrew.